Job Details
About the company H2Ok Innovations is an IoT platform for optimizing industrial liquid and fluid systems in supply chain and manufacturing. We unlock previously untapped data and drive data-driven decisions off this new information to provide our customers a competitive advantage in their operations, becoming more efficient and sustainable. Our IoT system consists of a network of versatile and scalable spectral-based proprietary sensors deployed in-line, connected to our ML edge compute models and gateway, coupled with our process insights software. We are bridging OT (operational technology) and IT (information technology) to provide data-driven optimization of facility performance in liquid-related processes (e.g., changeovers, cleaning/flushing, Clean-in-Place optimization, real-time product & ingredient QA/QC, wastewater optimization.) H2Ok Innovations is a woman-founded and BIPOC-founded cleantech startup based out of Greentown Labs, North America's largest cleantech incubator. Backed by Construct Capital, 2048 Ventures, Flybridge Capital, 1517 Fund, Techstars, and more, we are bringing Industry 4.0 and achieving significant strides in conserving water and optimizing manufacturing processes with major customers from Unilever (recognized as their top startup supplier of the year), to Cargill, Coca-Cola Company, Ecolab, Constellation Brands, and numerous other industrial enterprises.
Job description H2Ok seeks a highly motivated and skilled Data Scientist to join our team and contribute to finding meaning in challenging data. The role will focus on improving and designing new models to deploy on the factory floor, providing tangible process optimizations. The role's seniority will be determined based on assessment.
Responsibilities
Machine Learning Model Development
- Design, develop, and implement machine learning models and algorithms from sensor, facility, and operations real-time data to optimize and improve the functionality of decisions addressing waste reduction, production optimization, predictive maintenance, and environmental impact.
- Understand customer problem statements, goals, and industrial deployment process environments on a first principles level for the most effective model design.
Algorithm Optimization
- Optimize machine learning algorithms for constrained IoT device environments, considering limited computational resources, power, and memory constraints while maintaining high accuracy and performance Integration with IoT Devices
- Integrate machine learning models into IoT devices, ensuring seamless interaction and real-time decision-making based on collected sensor data.
- Deploy machine learning models within customer facilities.
Insights Communication
- Effectively present insights and results from data and models to external stakeholders such as customers and the internal team.
Continuous Improvement
- Continuously monitor and evaluate model performance, making data-driven improvements and updates to machine learning models in both development and production environments to enhance their accuracy, robustness, and adaptability.
- Develop data request, integration, and cleaning pipeline for model development.
Collaboration and Cross-Functional Communication
- Collaborate with cross-functional teams, including hardware engineers and software developers, to ensure successful integration of machine learning solutions into IoT devices. Research and Innovation
- Stay informed about the latest advancements in machine learning, artificial intelligence, and IoT technologies to identify and apply innovative solutions to improve our products. Documentation and Reporting
- Document machine learning models, algorithms, and integration processes and provide regular updates and reports to the team and management.
Qualifications
- Bachelor's or higher degree in Computer Science, Data Science, Machine Learning, or a related field.
- Proven experience developing machine learning models and implementing them in real-world applications, preferably in the IoT domain.
- Proficiency in Statistical Analysis fundamentals: collecting, organizing, cleaning, analyzing, and interpreting data.
- Strong programming skills in languages and experience with relevant machine learning libraries and frameworks (e.g., C, C++, Python, TensorFlow, PyTorch, scikit-learn, Google colab, pandas, plotly.)
- Solid understanding of machine learning algorithms, data structures, and statistical modeling.
- Familiarity with IoT platforms, sensors, embedded software, and data collection from IoT devices.
- Experience developing and deploying machine learning to edge applications.
- Proficiency with SQL; ability to create advanced queries, ETLs, functions, procedures, views, and temporary tables.
- Experience with Hardoop, Spark, and NoSQL.
- Experience with data preprocessing, feature engineering, and data visualization.
- Excellent problem-solving skills and ability to work in a collaborative team environment.
- Ability to understand industrial processes
- Strong communication skills and ability to present findings and insights effectively.
Preferred Skills
- Knowledge of edge computing and deploying machine learning models on IoT devices.
- Experience with cloud platforms for IoT and machine learning (e.g., AWS IoT, Azure IoT, Google Cloud IoT).
- Familiarity with sustainable and clean energy technologies or related domains.
- Understanding of environmental monitoring and sustainability applications.
Full-time position with competitive compensation and benefits.
www.h2okinnovations.com/careers